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Playing push vs pull: models and algorithms for disseminating dynamic data in networks

Published: 30 July 2006 Publication History

Abstract

Consider a network in which a collection of source nodes maintain and periodically update data objects for a collection of sink nodes, each of which periodically accesses the data originating from some specified subset of the source nodes. We consider the task of efficiently relaying the dynamically changing data objects to the sinks from their sources of interest. Our focus is on the following "push-pull" approach for this data dissemination problem. Whenever a data object is updated, its source relays the update to a designated subset of nodes, its push set; similarly, whenever a sink requires an update, it propagates its query to a designated subset of nodes, its pull set. The push and pull sets need to be chosen such that every pull set of a sink intersects the push sets of all its sources of interest. We study the problem of choosing push sets and pull sets to minimize total global communication while satisfying all communication requirements.We formulate and study several variants of the above data dissemination problem, that take into account different paradigms for routing between sources (resp., sinks) and their push sets (resp., pull sets) -- multicast, unicast, and controlled broadcast -- as well as the aggregability of the data objects. Under the multicast model, we present an optimal polynomial time algorithm for tree networks, which yields a randomized O(log n)-approximation algorithm for n-node general networks, for which the problem is hard to approximate within a constant factor. Under the unicast model, we present a randomized O(log n)-approximation algorithm for non-metric costs and a matching hardness result. For metric costs, we present an O(1)-approximation and matching hardness result for the case where the interests of any two sinks are either disjoint or identical. Finally, under the controlled broadcast model, we present optimal polynomial-time algorithms.While our optimization problems have been formulated in the context of data communication in networks, our problems also have applications to network design and multicommodity facility location and are of independent interest.

References

[1]
Y. Bartal. Probabilistic approximations of metric spaces and its algorithmic applications. In IEEE Symposium on Foundations of Computer Science, pages 184--193, 1996.
[2]
M. Charikar, C. Chekuri, A. Goel, and S. Guha. Rounding via trees: deterministic approximation algorithms for group Steiner trees and k-median. In Proc. 30th Annual ACM Symposium on Theory of Computing, pages 114--123, 1998.
[3]
M. Charikar, S. Guha, E. Tardos, and D. B. Shmoys. A constant-factor approximation algorithm for the k-median problem (extended abstract). In 31st Annual ACM Symposium on Theory of Computing, pages 1--10, 1999.
[4]
H. Chernoff. A measure of the asymptotic efficiency for tests of a hypothesis based on the sum of observations. Annals of Mathematical Statistics, 23:493--509, 1952.
[5]
M. Chlebík and J. Chlebíkovà. Approximation hardness of the steiner tree problem on graphs. In SWAT '02: Proceedings of the 8th Scandinavian Workshop on Algorithm Theory, pages 170--179, London, UK, 2002. Springer-Verlag.
[6]
Y. Dodis and S. Khanna. Designing networks with bounded pairwise distance. In 31st Annual ACM Symposium on Theory of Computing (STOC), pages 750--759, 1999.
[7]
J. Fakcharoenphol, S. Rao, and K. Talwar. A tight bound on approximating arbitrary metrics by tree metrics. In STOC '03: Proc. of the 35th annual ACM Symposium on Theory of computing, pages 448--455, New York, NY, USA, 2003. ACM Press.
[8]
M. R. Garey and D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. Freeman, New York, 1979.
[9]
M. X. Goemans and M. Skutella. Cooperative facility location games. In Symposium on Discrete Algorithms, pages 76--85, 2000.
[10]
S. Guha and S. Khuller. Greedy strikes back: Improved facility location algorithms. Journal of Algorithms, 31:228--248, 1999.
[11]
W. Hoeffding. Probability inequalities for sums of bounded random variables. Journal of the American Statistical Association, 58:13--30, 1963.
[12]
K. Jain and V. V. Vazirani. Primal-dual approximation algorithms for metric facility location and k-median problems. In IEEE Symposium on Foundations of Computer Science, pages 2--13, 1999.
[13]
G. Konjevod, R. Ravi, and F. S. Salman. On approximating planar metrics by tree metrics. Information Processing Letters, 80(4):213--219, 2001.
[14]
G. Kortsarz. On the hardness of approximating spanners. Algorithmica, 30(3):432--450, 2001.
[15]
G. Kortsarz and D. Peleg. Generating low-degree 2-spanners. SIAM Journal on Computing, 27(5):1438--1456, 1998.
[16]
J. H. Lin and J. S. Vitter. Approximation algorithms for geometric median problems. Information Processing Letters, 44:245--249, 1992. Tech Report CS-92-37.
[17]
X. Liu, Q. Huang, and Y. Zhang. Combs, needles, haystacks: balancing push and pull for discovery in large-scale sensor networks. In SenSys '04: Proceedings of the 2nd international conference on Embedded networked sensor systems, pages 122--133, New York, NY, USA, 2004. ACM Press.
[18]
R. Ravi and A. Sinha. Multicommodity facility location. In SODA '04: Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms, pages 342--349, Philadelphia, PA, USA, 2004. Society for Industrial and Applied Mathematics.
[19]
G. Reich and P. Widmayer. Beyond Steiner's problem: A VLSI oriented generalization. In Graph-Theoretic Concepts in Computer Science WG-89, Lecture Notes in Computer Science, volume 411, pages 196--210. Springer-Verlag, 1990.
[20]
D. Sandler, A. Mislove, A. Post, and P. Druschel. Feedtree: Sharing web micronews with peer-to-peer event notification. In Proceedings of the 4th International Workshop on Peer-to-Peer Systems (IPTPS'05), Ithaca, New York, Feb. 2005.
[21]
D. B. Shmoys, É. Tardos, and K. Aardal. Approximation algorithms for facility location problems (extended abstract). In 29th ACM Symposium on Theory of Computing, pages 265--274, 1997.
[22]
M. Sviridenko. An improved approximation algorithm for the metric uncapacitated facility location problem. In 9th IPCO, LNCS 2337, pages 240--257, 2002.
[23]
C. Swamy and A. Kumar. Primal-dual algorithms for connected facility location problems. In 5th International Workshop on Approximation Algorithms for Combinatorial Optimization (APPROX '02) LNCS 2462, pages 256--270, 2002.
[24]
D. P. Williamson, M. X. Goemans, M. Mihail, and V. V. Vazirani. A primal-dual approximation algorithm for generalized Steiner network problems. In Proc. of the 25th annual ACM symposium on Theory of computing, pages 708--717, 1993.
[25]
N. E. Young. K-medians, facility location, and the Chernoff-Wald bound. In ACM-SIAM Symposium on Discrete Algorithms, pages 86--95, 2000.

Cited By

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  • (2014)Push or pull? Toward optimal content delivery using cloud storageJournal of Network and Computer Applications10.5555/2773807.277404640:C(234-243)Online publication date: 1-Apr-2014
  • (2014)Push or pull? Toward optimal content delivery using cloud storageJournal of Network and Computer Applications10.1016/j.jnca.2013.09.00340(234-243)Online publication date: Apr-2014
  • (2012)Research on Information Dissemination in Urban Rail Transit Line NetworkEmerging Intelligent Computing Technology and Applications10.1007/978-3-642-31837-5_48(328-335)Online publication date: 2012
  • Show More Cited By

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cover image ACM Conferences
SPAA '06: Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
July 2006
344 pages
ISBN:1595934529
DOI:10.1145/1148109
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 30 July 2006

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Author Tags

  1. NP-Completeness
  2. approximation algorithms
  3. data dissemination
  4. multicast tree
  5. network design
  6. push & pull

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SPAA06
SPAA06: 18th ACM Symposium on Parallelism in Algorithms and Architectures 2006
July 30 - August 2, 2006
Massachusetts, Cambridge, USA

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Overall Acceptance Rate 447 of 1,461 submissions, 31%

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Cited By

View all
  • (2014)Push or pull? Toward optimal content delivery using cloud storageJournal of Network and Computer Applications10.5555/2773807.277404640:C(234-243)Online publication date: 1-Apr-2014
  • (2014)Push or pull? Toward optimal content delivery using cloud storageJournal of Network and Computer Applications10.1016/j.jnca.2013.09.00340(234-243)Online publication date: Apr-2014
  • (2012)Research on Information Dissemination in Urban Rail Transit Line NetworkEmerging Intelligent Computing Technology and Applications10.1007/978-3-642-31837-5_48(328-335)Online publication date: 2012
  • (2011)Multicommodity facility location under group Steiner access costProceedings of the twenty-second annual ACM-SIAM symposium on Discrete algorithms10.5555/2133036.2133113(996-1013)Online publication date: 23-Jan-2011
  • (2011)Push or Pull?: Toward Optimal Content Delivery2011 IEEE International Conference on Communications (ICC)10.1109/icc.2011.5963299(1-5)Online publication date: Jun-2011

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